polars.Expr.arr.contains#

Expr.arr.contains(item: IntoExpr, *, nulls_equal: bool = True) → Expr[source]#

Check if sub-arrays contain the given item.

engine:In MemoryStreamingDistributed

Parameters:

item: Item that will be checked for membership
nulls_equalbool, default True: If True, treat null as a distinct value. Null values will not propagate. Note that Expr.is_in() defaults to False.

Returns:

Expr: Expression of data type Boolean.

Notes

For supported dtype pairs, lossy conversions do not create matches. Values that would overflow or require rounding match nothing. Cast explicitly to compare integers and floats.

Examples

>>> df = pl.DataFrame(
...     {"a": [["a", "b"], ["x", "y"], ["a", "c"]]},
...     schema={"a": pl.Array(pl.String, 2)},
... )
>>> df.with_columns(contains=pl.col("a").arr.contains("a"))
shape: (3, 2)
┌───────────────┬──────────┐
│ a             ┆ contains │
│ ---           ┆ ---      │
│ array[str, 2] ┆ bool     │
╞═══════════════╪══════════╡
│ ["a", "b"]    ┆ true     │
│ ["x", "y"]    ┆ false    │
│ ["a", "c"]    ┆ true     │
└───────────────┴──────────┘